Tian Han - RankMe

59 papers A* 17A 5B 2Journal 31Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Improving Adversarial Energy-Based Model via Diffusion Process. ICML Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
2024	J	`jnl`	Improving Adversarial Energy-Based Model via Diffusion Process. CoRR Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
2024	A*	`conf`	Layerwise Change of Knowledge in Neural Networks. ICML Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2024	J	`jnl`	Layerwise Change of Knowledge in Neural Networks. CoRR Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2024	A*	`conf`	Learning Latent Space Hierarchical EBM Diffusion Models. ICML Jiali Cui, Tian Han
2024	J	`jnl`	Learning Latent Space Hierarchical EBM Diffusion Models. CoRR Jiali Cui, Tian Han
2024	—	`conf`	Learning Multimodal Latent Generative Models with Energy-Based Prior. ECCV (89) Shiyu Yuan, Jiali Cui, Hanao Li, Tian Han
2023	A*	`conf`	Learning Energy-based Model via Dual-MCMC Teaching. NeurIPS Jiali Cui, Tian Han
2023	J	`jnl`	Learning Energy-based Model via Dual-MCMC Teaching. CoRR Jiali Cui, Tian Han
2023	A*	`conf`	Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. ICCV Jiali Cui, Ying Nian Wu, Tian Han
2023	J	`jnl`	Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. CoRR Jiali Cui, Ying Nian Wu, Tian Han
2023	A*	`conf`	Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CVPR Jiali Cui, Ying Nian Wu, Tian Han
2023	J	`jnl`	Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CoRR Jiali Cui, Ying Nian Wu, Tian Han
2023	A	`conf`	Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. UAI Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
2023	J	`jnl`	Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. CoRR Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
2022	A*	`conf`	Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model. NeurIPS Zhisheng Xiao, Tian Han
2022	J	`jnl`	Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model. CoRR Zhisheng Xiao, Tian Han
2022	A*	`conf`	Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs. AAAI Chang Lu, Tian Han, Yue Ning
2022	J	`jnl`	Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry. IEEE Trans. Pattern Anal. Mach. Intell. Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
2022	A*	`conf`	Learning from the Tangram to Solve Mini Visual Tasks. AAAI Yizhou Zhao, Liang Qiu, Pan Lu, Feng Shi, Tian Han, Song-Chun Zhu
2021	J	`jnl`	Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs. CoRR Chang Lu, Tian Han, Yue Ning
2021	J	`jnl`	GenMotion: Data-driven Motion Generators for Real-time Animation Synthesis. CoRR Yizhou Zhao, Wensi Ai, Liang Qiu, Pan Lu, Feng Shi, Tian Han, Song-Chun Zhu
2021	A	`conf`	Generative Text Modeling through Short Run Inference. EACL Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	J	`jnl`	Generative Text Modeling through Short Run Inference. CoRR Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	A	`conf`	Lavs: A Lightweight Audio-Visual Saliency Prediction Model. ICME Dandan Zhu, Defang Zhao, Xiongkuo Min, Tian Han, Qiangqiang Zhou, Shaobo Yu, Yongqing Chen, Guangtao Zhai, Xiaokang Yang
2021	J	`jnl`	Learning from the Tangram to Solve Mini Visual Tasks. CoRR Yizhou Zhao, Liang Qiu, Pan Lu, Feng Shi, Tian Han, Song-Chun Zhu
2021	J	`jnl`	Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
2021	J	`jnl`	STAR: Sparse Transformer-based Action Recognition. CoRR Feng Shi, Chonghan Lee, Liang Qiu, Yizhou Zhao, Tianyi Shen, Shivran Muralidhar, Tian Han, Song-Chun Zhu, Vijaykrishnan Narayanan
2021	J	`jnl`	Towards multi-scale deep features learning with correlation metric for person re-identification. Knowl. Based Syst. Dandan Zhu, Qiangqiang Zhou, Tian Han, Yongqing Chen, Defang Zhao, Xiaokang Yang
2020	A*	`conf`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CVPR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CoRR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Latent Space Energy-Based Prior Model for Molecule Generation. CoRR Bo Pang, Tian Han, Ying Nian Wu
2020	A*	`conf`	Learning Latent Space Energy-Based Prior Model. NeurIPS Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Latent Space Energy-Based Prior Model. CoRR Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	—	`conf`	Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference. ECCV (6) Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models. AAAI Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2020	A	`conf`	Ransp: Ranking Attention Network For Saliency Prediction On Omnidirectional Images. ICME Dandan Zhu, Yongqing Chen, Tian Han, Defang Zhao, Yucheng Zhu, Qiangqiang Zhou, Guangtao Zhai, Xiaokang Yang
2020	B	`conf`	Saliency Prediction on Omnidirectional Images with Brain-Like Shallow Neural Network. ICPR Dandan Zhu, Yongqing Chen, Xiongkuo Min, Defang Zhao, Yucheng Zhu, Qiangqiang Zhou, Xiaokang Yang, Tian Han
2020	J	`jnl`	Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling. CoRR Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu
2019	J	`jnl`	360 Degree Panorama Synthesis From Sequential Views Based on Improved FC-Densenets. IEEE Access Dandan Zhu, Qiangqiang Zhou, Tian Han, Yongqing Chen
2019	J	`jnl`	Deep Unsupervised Clustering with Clustered Generator Model. CoRR Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu
2019	A*	`conf`	Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model. CVPR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Learning Deep Generative Models with Short Run Inference Dynamics. CoRR Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2019	A	`conf`	Learning Generator Networks for Dynamic Patterns. WACV Tian Han, Yang Lu, Jiawen Wu, Xianglei Xing, Ying Nian Wu
2019	J	`jnl`	On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models. CoRR Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Replicating Neuroscience Observations on ML/MF and AM Face Patches by Deep Generative Model. Neural Comput. Tian Han, Xianglei Xing, Jiawen Wu, Ying Nian Wu
2019	A*	`conf`	Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network. CVPR Xianglei Xing, Tian Han, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
2019	—	`—`	Unsupervised Learning and Understanding of Deep Generative Models. Tian Han
2018	J	`jnl`	A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models. CoRR Ying Nian Wu, Ruiqi Gao, Tian Han, Song-Chun Zhu
2018	J	`jnl`	Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry. CoRR Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model. CoRR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2018	B	`conf`	Learning Multi-view Generator Network for Shared Representation. ICPR Tian Han, Xianglei Xing, Ying Nian Wu
2018	A*	`conf`	Replicating Active Appearance Model by Generator Network. IJCAI Tian Han, Jiawen Wu, Ying Nian Wu
2018	J	`jnl`	Replicating Active Appearance Model by Generator Network. CoRR Tian Han, Jiawen Wu, Ying Nian Wu
2018	J	`jnl`	Survey on person re-identification based on deep learning. CAAI Trans. Intell. Technol. Kejun Wang, Haolin Wang, Meichen Liu, Xianglei Xing, Tian Han
2017	A*	`conf`	Alternating Back-Propagation for Generator Network. AAAI Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2016	J	`jnl`	Learning Generative ConvNet with Continuous Latent Factors by Alternating Back-Propagation. CoRR Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu
2012	A*	`conf`	Parsing façade with rank-one approximation. CVPR Chao Yang, Tian Han, Long Quan, Chiew-Lan Tai
2012	—	`conf`	Quasi-regular Facade Structure Extraction. ACCV (4) Tian Han, Chun Liu, Chiew-Lan Tai, Long Quan